Reasoning and Planning
Reasoning is the process of drawing conclusions from existing knowledge. Planning is a specific type of reasoning that involves deciding on a sequence of actions to achieve a goal. Together, they enable intelligent behavior.
Types of Reasoning
- Deductive reasoning: General rule → specific conclusion. Example: All humans are mortal. Socrates is human. Therefore, Socrates is mortal.
- Inductive reasoning: Specific observations → general rule. Example: Every swan we have seen is white → All swans are white. (Not always true!)
- Abductive reasoning: Observation → best explanation. Example: Grass is wet → It rained last night (or sprinklers were on).
- Analogical reasoning: Compare two similar situations. Example: Mars is like Earth, so it might have life.
What is Planning?
Planning is a subfield of AI that deals with finding a sequence of actions to achieve a goal. It requires:
- Initial state: Where we start.
- Goal state: What we want to achieve.
- Actions: Possible moves with preconditions and effects.
- Plan: Ordered list of actions.
Example: Planning a Trip
Initial: at home, no tickets.
Goal: at airport, have ticket.
Actions: drive to station, buy ticket, board train, etc.
Plan: {drive to station, buy ticket, board train, ...}
Classic AI Planning Example: Blocks World
A robot arm can pick up and stack blocks. Initial: blocks A, B, C on table. Goal: stack A on B on C. The planner finds the sequence: pick A, put on B, pick B, put on C, etc.
Real‑World Applications
- Autonomous robots (planning paths)
- Game playing (chess, Go)
- Logistics (route planning for delivery)
- Personal assistants (scheduling meetings)
Two Minute Drill
- Reasoning draws conclusions from knowledge (deductive, inductive, abductive, analogical).
- Planning finds sequences of actions to achieve goals.
- Key planning elements: initial state, goal state, actions.
- Applications: robotics, games, logistics, scheduling.
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